skip to main content
10.1145/3588028.3603649acmconferencesArticle/Chapter ViewAbstractPublication PagessiggraphConference Proceedingsconference-collections
poster

Virtual Manipulation of Cultural Assets: An Initial Case Study with Single-Joint Articulated Models

Published:23 July 2023Publication History

ABSTRACT

Virtual space can eliminate the physical constraints of real space. Three-dimensional (3D) digital twins enable us to experience manipulation of cultural assets that are inaccessible in real space. However, most 3D models obtained using current reconstruction techniques are static; they cannot be manipulated dynamically. In this study, we reproduce a dynamic 3D model of a simple articulated object with a rotating joint from a static point cloud only with reference to a video of the motion and a manually added rotation axis. The reconstructed actual cultural asset is used for first-person experiences in an augmented reality environment.

Skip Supplemental Material Section

Supplemental Material

Shinji_Video_final.MP4

MP4

149.8 MB

References

  1. Michael Kazhdan, Matthew Bolitho, and Hugues Hoppe. 2006. Poisson Surface Reconstruction. In Proc. SGP 2006. 61–70.Google ScholarGoogle Scholar
  2. Xiaolong Li, He Wang, Li Yi, Leonidas J. Guibas, A. Lynn Abbott, and Shuran Song. 2020. Category-Level Articulated Object Pose Estimation. In Proc. CVPR 2020. 3703–3712.Google ScholarGoogle ScholarCross RefCross Ref
  3. Ruwen Schnabel, Roland Wahl, and Reinhard Klein. 2007. Efficient RANSAC for Point-Cloud Shape Detection. Computer Graphics Forum 26, 2 (2007), 214–226.Google ScholarGoogle ScholarCross RefCross Ref
  4. Li Yi, Haibin Huang, Difan Liu, Evangelos Kalogerakis, Hao Su, and Leonidas Guibas. 2018. Deep Part Induction from Articulated Object Pairs. ACM Transactions on Graphics 37, 6, Article 209 (2018).Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Virtual Manipulation of Cultural Assets: An Initial Case Study with Single-Joint Articulated Models

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      SIGGRAPH '23: ACM SIGGRAPH 2023 Posters
      July 2023
      111 pages
      ISBN:9798400701528
      DOI:10.1145/3588028

      Copyright © 2023 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 23 July 2023

      Check for updates

      Qualifiers

      • poster
      • Research
      • Refereed limited

      Acceptance Rates

      Overall Acceptance Rate1,822of8,601submissions,21%

      Upcoming Conference

      SIGGRAPH '24
    • Article Metrics

      • Downloads (Last 12 months)61
      • Downloads (Last 6 weeks)2

      Other Metrics

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    HTML Format

    View this article in HTML Format .

    View HTML Format